Jobs at YipitData

Lead and develop a team of product managers while owning strategy, execution, and commercial performance for a portfolio of B2B data feeds. Directly manage a strategic data product, guide customer discovery, prioritize investments, partner with Data, Engineering, Quant Research, and commercial teams, and improve data quality, integration, onboarding, adoption, retention, and revenue outcomes.

Own end-to-end US payroll for 500+ employees, including multi-state compliance, tax requirements, benefits deductions, invoice reconciliation, and self-insured plan activity. Partner with Finance, People Ops, ADP, and benefits vendors to resolve discrepancies, support audits, W-2 preparation, open enrollment, and reconciliations. Maintain controls, documentation, and recurring processes while identifying opportunities to automate and scale payroll and benefits operations.

Target and break into large enterprise accounts (>$100M software spend) using outbound prospecting (cold calls, emails, LinkedIn) to generate meetings with procurement leaders. Use modern sales tools, collaborate with sales leadership and enablement, refine messaging, and develop toward full end-to-end sales responsibility.

Analyze large datasets using SQL and Python, maintain recurring analyses and data products, perform quality checks, investigate discrepancies, and identify trends. Collaborate with Research, Engineering, and Product teams to resolve data issues, document findings, and improve analytical workflows through automation and AI tools. The role is designed for an early-career analyst who is detail-oriented, curious, and interested in using data to inform investment decisions.

Lead modernization and scaling of YipitData’s AWS cloud infrastructure, Kubernetes platform, Terraform ecosystem, SRE, DevOps, and developer experience. Manage a global player-coach team, establish reliability and disaster-recovery practices, improve platform adoption and engineering velocity, create sustainable 24/7 operations, and optimize cloud costs while maintaining reliability.

Leads the emerging sector insights team, owning product strategy and roadmaps for key categories, managing and developing insights analysts, and driving sector commercial success through collaboration on upsell and renewal opportunities. The role combines market research, client service, data analysis, cross-functional collaboration, and thought leadership. It is remote-friendly within the United States and requires East or West Coast work hours.

Own and maintain data products end-to-end for sector teams, analyze large datasets, refine methodologies, automate workflows using AI and tooling, collaborate with Research, Engineering, and Product, and deliver accurate, client-facing insights and improvements.

Own Kepler’s transaction data feed end-to-end, ensuring accuracy, improving methodologies, developing QA frameworks, solving complex analytical problems, and prototyping enhancements. Analyze massive datasets, automate workflows with AI, evaluate client-facing AI outputs, address high-complexity customer questions, and collaborate with Research, Product, Data Science, and Engineering teams.

Conduct outbound prospecting through cold calls, emails, LinkedIn, and other channels; qualify inbound and marketing-qualified leads; communicate product value; collaborate with Sales, Product, GTM Engineering, and Marketing; map decision-makers and personas; and use sales technology to expand markets and generate new business.

Leads engineering for ERP data management, high-volume email processing, backend APIs, distributed systems, and service architecture. Owns reliability, scalability, security, observability, and iterative platform improvements for 24/7 systems. Acts as a liaison between engineering and business teams, mentors engineers, and collaborates across global teams in India, China, Singapore, and the United States. The role is fully remote from India and requires flexibility for global operations.

Own YipitAgent’s product-led growth motion across acquisition, trial activation, engagement, conversion, retention, and re-engagement. Optimize SEO/AEO, onboarding, in-product education, lifecycle communications, pricing, packaging, and trial experiences. Use customer research, behavioral data, funnel metrics, cohorts, and experimentation to identify growth opportunities. Partner with product, design, engineering, data, marketing, sales, and customer teams to launch, measure, and iterate on experiences that increase trials, active usage, and paid conversion.

Own high-impact data products, ingestion pipelines, and granular data feeds end to end. Analyze massive datasets to answer client and stakeholder questions, ensure data accuracy, and derive actionable insights. Improve products and pipelines by developing methodologies, scaling third-party datasets, and creating data modules. The role requires clear communication, attention to detail, methodical problem solving, prioritization, experimentation, and strong ownership. Training includes SQL, PySpark, Python fundamentals, and internal tools.

Drive discovery, development, commercialization, and improvement of alternative data products. Evaluate and source datasets, collaborate with Partnerships and Revenue teams, conduct client research, shape product strategy, communicate roadmaps, and potentially build and manage a Product Development Analyst team. The role focuses on expanding revenue and client engagement through innovative data experiences and requires strong understanding of financial client needs and data technology.

Lead revenue growth by selling alternative data feed products to quantitative hedge funds and systematic investment firms. Own the full sales cycle from prospecting and qualification through contract execution, build pipeline through outreach and industry relationships, tailor solutions with product teams, exceed sales quotas, and represent the company at conferences and client meetings.

Leads a web scraping engineering team and owns scraping infrastructure architecture, scalability, reliability, performance, monitoring, and data quality. Manages scrapers using Playwright, Puppeteer, and Selenium; solves dynamic-site, browser automation, fingerprinting, session, cookie, header, and proxy challenges. Mentors engineers, drives technical standards and planning, collaborates with Engineering, Data, Analytics, and Product teams, and participates in hiring and technical reviews.

The Product Security Engineer partners with Engineering and Product teams to embed security throughout the development lifecycle. Responsibilities include threat modeling, architecture and security reviews, vulnerability validation, remediation planning, security-tool ownership, automation, secure coding guidance, incident response, and assessing risks in cloud and AI-enabled products. The role requires strong application security, identity, authentication, authorization, coding, communication, and cross-functional collaboration skills.

Design, build, refactor, and maintain resilient web scrapers for large-scale data extraction. Apply advanced fingerprinting and evasion techniques, manage dynamic content, sessions, cookies, headers, and proxy rotations, and optimize scraper reliability and scalability. Develop monitoring, logging, metrics, and alerting systems; troubleshoot failures and bottlenecks; collaborate with analysts and stakeholders on requirements and data quality; and document best practices and continuously improve scraping tools and methodologies.

Manages the full accounts receivable cycle, including invoicing, collections, cash application, reconciliations, discrepancy resolution, and customer communications. Reviews APAC payroll transactions in NetSuite, supports month-end close, prepares journal entries and account reconciliations, analyzes financial variances, and assists with annual audits and special accounting projects.

The Data Product Analyst will own Signals data products, work with AI and Data Engineering, ensure data quality, conduct analyses, and shape product improvements through client feedback.

Own product positioning and go-to-market strategy for YipitData’s AI and big data products serving public investors. Define customer segments and messaging, lead product launches, conduct competitive intelligence, support pricing and packaging, and create sales enablement materials. Partner with Product, Revenue, and Insights teams to shape the roadmap and drive adoption. Establish GTM success metrics, monitor performance, and improve strategies across data feeds, software, and AI-powered investor solutions.